Q-omics provides the consensus-scored DHFR profile across patient tissues and cancer cell-line models. DHFR expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, DHFR is differentially expressed in 13, with the highest sampling consensus in LUAD. Additionally, DHFR protein abundance shows 24,590 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, LUAD, and GBM as cancer lineages where DHFR shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for DHFR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes DHFR survival associations across molecular data types. DHFR RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible DHFR RNA expression–survival associations across cancer types. High DHFR expression shows unfavorable associations in ACC, KICH, UVM and KIRP, but favorable associations in KIRC and READ. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for DHFR RNA expression.
This table summarizes DHFR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for DHFR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. DHFR shows higher tumor expression in LUAD, HNSC, STAD, LUSC, UCEC and BRCA. The LUAD box plot shows higher DHFR RNA expression in tumor versus normal tissue (log2 FC = +1.026, t-test p < 0.001).
This table shows molecular features associated with DHFR in patient tissues and cancer cell lines. In patient samples, DHFR shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, DHFR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
